Andy Liaw

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 11

Top Topics

Gradient Boosting

Top Venues

J. Chem. Inf. Model.

Publications

Annie Liang, Thomas Jemielita, Andy Liaw, Vladimir Svetnik, Lingkang Huang, Richard Baumgartner, Jason M. Klusowski
Challenges in Variable Importance Ranking Under Correlation. CoRR (2024)
Yuting Xu, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik
Development and Evaluation of Conformal Prediction Methods for QSAR. CoRR (2023)
Robert P. Sheridan, Andy Liaw, Matthew Tudor
Light Gradient Boosting Machine as a Regression Method for Quantitative Structure-Activity Relationships. CoRR (2021)
Robert P. Sheridan, Min Wang, Andy Liaw, Junshi Ma, Eric M. Gifford
Correction to Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 60 (3) (2020)
Robert P. Sheridan, Prabha Karnachi, Matthew Tudor, Yuting Xu, Andy Liaw, Falgun Shah, Alan C. Cheng, Elizabeth Joshi, Meir Glick, Juan Alvarez
Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure-Activity Relationship Models? J. Chem. Inf. Model. 60 (4) (2020)
Anthony Difranzo, Robert P. Sheridan, Andy Liaw, Matthew Tudor
Nearest Neighbor Gaussian Process for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 60 (10) (2020)
Yuting Xu, Deeptak Verma, Robert P. Sheridan, Andy Liaw, Junshui Ma, Nicholas M. Marshall, John McIntosh, Edward C. Sherer, Vladimir Svetnik, Jennifer M. Johnston
Deep Dive into Machine Learning Models for Protein Engineering. J. Chem. Inf. Model. 60 (6) (2020)
Dai Feng, Vladimir Svetnik, Andy Liaw, Matthew T. Pratola, Robert P. Sheridan
Building Quantitative Structure-Activity Relationship Models Using Bayesian Additive Regression Trees. J. Chem. Inf. Model. 59 (6) (2019)
Huijun Wang, Francisco Garcia, An Chi, Ivan Cornella Taracido, Anne Mai Wasssermann, Andy Liaw
Profiling Diverse Chemical Space to Map the Druggable Proteome. BCB (2018)
Yuting Xu, Junshui Ma, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik
Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 57 (10) (2017)
Robert P. Sheridan, Wei Min Wang, Andy Liaw, Junshui Ma, Eric M. Gifford
Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 56 (12) (2016)
Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik
Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 55 (2) (2015)
Junshui Ma, Christopher Tong, Andy Liaw, Robert P. Sheridan, John Szumiloski, Vladimir Svetnik
Generating hypotheses about molecular structure-activity relationships (SARs) by solving an optimization problem. Stat. Anal. Data Min. 2 (3) (2009)
Vladimir Svetnik, Ting Wang, Christopher Tong, Andy Liaw, Robert P. Sheridan, Qinghua Song
Boosting: An Ensemble Learning Tool for Compound Classification and QSAR Modeling. J. Chem. Inf. Model. 45 (3) (2005)
Vladimir Svetnik, Andy Liaw, Christopher Tong, Ting Wang
Application of Breiman's Random Forest to Modeling Structure-Activity Relationships of Pharmaceutical Molecules. Multiple Classifier Systems (2004)
Vladimir Svetnik, Andy Liaw, Christopher Tong, J. Christopher Culberson, Robert P. Sheridan, Bradley P. Feuston
Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling. J. Chem. Inf. Comput. Sci. 43 (6) (2003)